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Found 13 papers, 6 papers with code
Layer-Wise Feature Metric of Semantic-Pixel Matching for Few-Shot Learning
In Few-Shot Learning (FSL), traditional metric-based approaches often rely on global metrics to compute similarity.
IMAN: An Adaptive Network for Robust NPC Mortality Prediction with Missing Modalities
Accurate prediction of mortality in nasopharyngeal carcinoma (NPC), a complex malignancy particularly challenging in advanced stages, is crucial for optimizing treatment strategies and improving patient outcomes.
TAGE: Trustworthy Attribute Group Editing for Stable Few-shot Image Generation
The CPM module delves into the semantic dimensions of category-agnostic attributes, encapsulating them within a discrete codebook.
Lagrange Duality and Compound Multi-Attention Transformer for Semi-Supervised Medical Image Segmentation
Overall, our results indicate that CMAformer, combined with the feature fusion framework and the new consistency loss, demonstrates strong complementarity in semi-supervised learning ensembles.
Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning
Additionally, a multi-scale Transformer denoising module is constructed to leverage multi-scale convolution blocks and cross-attention-based diffusion Transformer blocks for conditional guidance to generate subject-adaptive SR EEG.
Multi-scale Quaternion CNN and BiGRU with Cross Self-attention Feature Fusion for Fault Diagnosis of Bearing
In this work, we propose a novel FD model by integrating multi-scale quaternion convolutional neural network (MQCNN), bidirectional gated recurrent unit (BiGRU), and cross self-attention feature fusion (CSAFF).
Medical Visual Prompting (MVP): A Unified Framework for Versatile and High-Quality Medical Image Segmentation
This novel framework offers improved performance with fewer parameters and holds significant potential for accurate segmentation of lesion regions in various medical tasks, making it clinically valuable.
Adaptive Query Prompting for Multi-Domain Landmark Detection
Thanks to the lightweight nature of the decoder and AQP, we can handle multiple datasets by sharing the backbone encoder and then only perform partial parameter tuning without incurring much additional cost.
Rotate to Scan: UNet-like Mamba with Triplet SSM Module for Medical Image Segmentation
Image segmentation holds a vital position in the realms of diagnosis and treatment within the medical domain.
PVALane: Prior-Guided 3D Lane Detection with View-Agnostic Feature Alignment
Monocular 3D lane detection is essential for a reliable autonomous driving system and has recently been rapidly developing.
Ranked #3 on
3D Lane Detection
on OpenLane
QEAN: Quaternion-Enhanced Attention Network for Visual Dance Generation
The study of music-generated dance is a novel and challenging Image generation task.
RBA-GCN: Relational Bilevel Aggregation Graph Convolutional Network for Emotion Recognition
This module can construct the interaction between different modalities and capture long-range contextual information based on similarity clusters.
Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation
In this paper, we introduce a quaternion perspective on correlation learning and propose a novel Quaternion-valued Correlation Learning Network (QCLNet), with the aim to alleviate the computational burden of high-dimensional correlation tensor and explore internal latent interaction between query and support images by leveraging operations defined by the established quaternion algebra.
Ranked #28 on
Few-Shot Semantic Segmentation
on COCO-20i (5-shot)
